DBMS > atoti vs. Linter vs. Pinecone vs. Postgres-XL

System Properties Comparison atoti vs. Linter vs. Pinecone vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

RDBMS for high security requirements

A managed, cloud-native vector database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

Technical documentation

docs.atoti.io

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

Developer

ActiveViam

relex.ru

Pinecone Systems, Inc

Initial release

1990

2019

2014

since 2012, originally named StormDB

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

distributed, parallel query execution

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Python

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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